Evaluating Energy Efficiency and Performance of Social-Based Routing Protocols in Delay-Tolerant Networks

Energy consumption is a significant issue for data forwarding in Delay-Tolerant Network (DTN), where nodes are energy-constrained as they are driven by batteries. During their limited lifetime, these nodes have to spend a huge amount of energy since they perform forwarding, receiving, and temporarily storing messages, searching for the neighboring nodes for message forwarding, etc. The remaining energy of a node is expected to be higher as it increases the possibility of successful message delivery. Hence, awareness of energy expenditure is necessary for the routing strategies in DTN. This issue instigated us to evaluate the impact of node remaining energy on social-based routing protocols for the DTN scenario. Apart from the conventional DTN forwarding techniques, social-based forwarding protocols have involved an emerging concept that considers nodes’ social relations and behaviors to make routing decisions for efficient message transmission. In this paper, we have analyzed the energy efficiency of several social-based routing approaches, such as Social-aware Content-based Opportunistic Routing Protocol (SCORP), dLife, dLifeComm, and Bubble Rap with their corresponding performance evaluations regarding the performance metrics: average remaining energy, delivery ratio, average delay, and transmission cost. Opportunistic Network Environment (ONE) simulator is used as the simulation tool, where all the simulations are performed by (i) varying the number of nodes in each group with a fixed message Time-To-Live (TTL), and (ii) changing the message TTL, while the number of nodes per group is kept constant. From the outcome of simulations, it is observed that SCORP has the highest energy efficiency and shows the best performances for average delay and transmission cost.